{"id":"W2993683594","doi":"","title":"Mapping peatland pools to improve estimations of carbon store on a boreal peatland in Canada","year":2014,"lang":"en","type":"article","venue":"EGU General Assembly Conference Abstracts","topic":"Peatlands and Wetlands Ecology","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Peat; Boreal; Environmental science; Bog; Physical geography; Taiga; Geography; Forestry; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002562358,0.0002190031,0.0003337905,0.00008824416,0.00006260044,0.00003091094,0.0002869314,0.00008463898,0.00009391466],"category_scores_gemma":[0.0001011521,0.0001919256,0.00003483301,0.0001944784,0.00003773421,0.00008489202,0.0001018233,0.0001899293,0.00001953942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003900108,"about_ca_system_score_gemma":0.0002639666,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7760935,"about_ca_topic_score_gemma":0.9256977,"domain_scores_codex":[0.9982842,0.00006512825,0.0004213246,0.0004199741,0.0003298892,0.0004794945],"domain_scores_gemma":[0.9991799,0.0001095859,0.0001592462,0.0002975017,0.00002408958,0.0002296862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007334333,0.0001468661,0.8671943,0.00002513804,0.00002201237,0.00005067296,0.0006783069,0.04557838,0.066374,0.0002620771,0.003251605,0.01634333],"study_design_scores_gemma":[0.0005272206,0.000202724,0.9862121,0.00003528419,0.000005879511,0.000004686684,0.00006736458,0.008338729,0.002823832,0.0001600542,0.001379392,0.0002427771],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9595252,0.000002573743,0.00006882455,0.0009207288,0.0001619684,0.0002471014,0.00002060843,0.00001309681,0.03903995],"genre_scores_gemma":[0.9986451,0.000003761181,0.000463872,0.0003160978,0.00008494339,0.00003514284,0.00005840585,0.00001256809,0.0003801239],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1496041,"threshold_uncertainty_score":0.7826498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173735933478136,"score_gpt":0.2209935274329993,"score_spread":0.2092561680982179,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}